Tryrating Exam Question and Answer | Map Evaluator/Data Analyst for Telus, Peroptyx, Oneforma, Appen

Welcome to the map evaluation tri rating

exam. This project is offered by various

companies including Telus, one forma,

peroptics, crowen also known as appen

and so on. Depending on the platform, it

may be referred to as data analyst,

milky way Mars or Kyper exam, but all

are the same map evaluation on the try

rating platform. Quick disclaimer before

we begin. This video is created strictly

for educational andformational purposes

only. It is not affiliated with,

sponsored by or endorsed by Tri Rating,

Telus, One Forma, Paroptics or Appen.

Now, let's dive in. If you've ever used

Google Maps or another navigation

service, you know how important it is to

get accurate results. When you type

coffee shop near me, you want real open

businesses with the correct name,

address, and location pin. That's

exactly what map raters help ensure. In

this video, we'll explore how try rating

works, how to interpret user intent, how

to rate results for relevance, accuracy,

and pin placement, and finally, how to

apply best practices so your ratings are

consistent and professional. Whether

you're completely new or you've already

done some MAP rating before, this video

will give you a solid foundation, walk

you through the guidelines step by step,

and help you pass your exams. All you

need to do is pay close attention.

Before you can rate any result, you need

to understand what the user actually

wants. This is called user intent. There

are different query types. address

queries like 717 El Camino Rel Sunnyvil,

business queries such as Starbucks, Yaba

Lagos, category queries, for example,

gyms near me or coffee shops, transit

queries like bus stop Maryland, and

sometimes even emoji queries for pizza

or for gas. Now, intent can be explicit

or implicit. Explicit intent is clear.

If someone types Barkclay's Banklist

Lester, we know exactly what they want.

Implicit intent depends on context. For

example, if the query is just Chinese,

the system must use the user's location

or viewport to understand if they want

Chinese restaurants nearby. As a raider,

your job is to combine the query, the

user's location, the viewport, and your

own judgment to determine intent. If

intent is unclear, you may need to

research using official sources like

business websites, postal services, or

government listings. Once you understand

intent, the next step is relevance.

Relevance means how well does the

results satisfy what the user was asking

for. Here are the main categories.

Navigational, when the query clearly

points to one unique place like Eiffel

Tower. Excellent. The result perfectly

satisfies intent, but it's not a unique

case. Good partially satisfies the

intent, but has issues with distance,

prominence, or secondary intent.

Acceptable technically matches, but in a

poor or unlikely way. Bad does not

satisfy the intent at all. Let's take

some quick examples. Query Starbucks

Paris 7502.

If the result shows a Starbucks at that

exact address, that's excellent. Query

fast fod misspelled. If the result shows

fast food restaurants nearby, that's

excellent because the intent was

corrected. Query New York. The city

itself is navigational, while results

like New York pizza may be rated lower

since they don't match the main intent.

Remember, even if a business is closed,

you still rate relevance as if it were

open. Data accuracy is handled

separately. Now let's talk about pin

accuracy. One of the most critical parts

of map evaluation. A pin should mark the

exact location of a business or feature.

The tip of the pin, not the head,

represents the precise spot. Here's what

you'll check for. Is the pin placed on

the correct building? If it's a large

campus like a university, is the pin

correctly placed at the main entrance or

within the right complex? For

residential areas, does the pin point to

the right house number? For natural

features like rivers or parks, does the

pin match the boundary? Common issues

include pins placed on the wrong side of

the street, pins floating in the middle

of a road, or pins marking the wrong

building entirely. If the pin is clearly

off, rate it as wrong. If you can't

verify due to lack of resources, use

can't verify. Remember, pin accuracy is

separate from relevance. Even a perfect

business listing can fail if the pin is

in the wrong place. Now, let's return to

navigational queries. Navigational

queries are those where the user expects

one unique result. For example, Taj

Mahal, Union Bank Marina, Lagos, Chering

Cross Station London. In these cases,

only one result can fully satisfy

intent. So, you'll answer the

navigational question. Is there a real

world result that completely satisfies

the user's intent? If yes, mark it

navigational. If no, mark it

accordingly. Other results may still get

rated excellent or good, but only one

can truly be the navigational target.

Here's a key tip. Navigational intent is

rare for category queries. For instance,

if someone types restaurants in New

York, there isn't a single unique

result. It's a set of options. Now,

let's put it all together and walk

through how to use the rating tool. For

each query, you'll see the query header

showing what the user typed, their

location, and viewport. The results list

each with a name, address, category, and

pin. The map interface with pins, user

location, and viewport. Here's the

workflow. One, first determine user

intent. Two, answer the navigational

question if applicable. Three, for each

result, check relevance. Four, if you're

rating in search 2.0, also check name

accuracy, category accuracy, address

accuracy, and pin accuracy. Five,

provide comments for any rating below.

Excellent. Keep them short, specific,

and in English. Example

query 357 Western Avenue Sweet 1. Result

357 Western Avenue Sweet 2. Relevance

equals good. Comment different unit

number satisfies intent partially. Let's

talk about name accuracy. What is name

accuracy? Let's start with the basics.

Name accuracy means checking whether the

name of a business or point of interest

matches the real world official name

that users would expect to see. For

example, a search for Target Sunnyvale

should return Target, not Target

Corporation retail store Sunnyvale. A

listing for McDonald's in Chicago should

appear as McDonald's, not McDonald's

burger restaurant or fast food place.

The goal is to make sure names are

precise, recognizable, and not

misleading. Now, let's talk about what

counts as a correct name. A correct name

is one that matches the business's real

world signage or its official online

presence, like the company website,

Google business profile, or Yelp page.

Example one. Query Starbucks Palo Alto.

Result: Starbucks. Correct. matches the

official business name. Example two.

Query, Whole Foods Market, San Diego.

Result, Whole Foods Market. Correct.

Exactly how the store identifies itself.

Example three. Query, Best Buy

Manhattan. Result, Best Buy. Correct. No

extra or missing words. Even if the

query includes extra details like city

names, the result title should just be

the business name, not an embellished

version. Sometimes a result name is

close but not fully accurate. These are

partially correct names and you'll need

to decide if it's a minor issue or a

moderate one. Minor misspellings.

Starbucks instead of Starbucks. Walmart

instead of Walmart. Note, Walmart

officially dropped the hyphen years ago.

These should be rated partially correct

because it's minor. Moderate issues.

Best Buy electronic superstore instead

of just Best Buy. Target supermarket

when the brand name is just Target.

These are partially correct. Moderate